Cluster analysis is the term applied to a group of analyses that seek to divide a set of objects into a number of homogeneous groups or clusters, when there no a priori information about the group structure of the data. Clustering is an active research topic in data mining and different methods have been proposed in the literature. Most of these methods are based on the use of a distance measure defined either on numerical attributes or on categorical attributes. There are three basic categories of clustering methods: partitional methods, hierarchical methods and density-based methods. This paper proposes an iterative algorithm for partitional clustering.
Patra, S. S. and .Dash, S. R.
"Partitional Clustering - An Iterative Algorithm,"
International Journal of Computer and Communication Technology: Vol. 3:
2, Article 5.
Available at: https://www.interscience.in/ijcct/vol3/iss2/5